Video games, movies and health care are some of the industries that rely on motion capture for enhanced experience and accurate prediction of movement of objects. Recent growth in camera technologies, and advancement in related research have proved vision as a primary sensor model for various applications which require human behavior characterization. In the past few decades, there has been an exponential growth in applications related to market research, health care, surveillance, and the like. An automatic approach for analyzing visual data for human behavior analysis offers two primary advantages. Firstly, subtle behavior details can be captured which otherwise may remain unnoticed. Secondly, an entire video can be summarized in much less time detecting all events in the duration under consideration. Hence it is imperative that movement is tracked precisely and in real time.